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With regard to that, I'd highly recommend Fatal Passage by Ken McGoogan, which is a biography of arctic explorer John Rae, who conducted the search for the Franklin expedition (and probably could have rescued them if things had worked out just a little bit differently) and discovered the final link in the northwest passage that Amundsen used 50 years later.

In every single case I crossed a border as a minor it was with free will and full paperwork, so I can't say if the screening was diligent in a way that would uncover a coercive crossing situation.

It also doesn't tell me anything about their screening criteria. Making too many type 2 errors, like I experienced with my grandparents, means that resources are not being effectively directed. And that has costs as well, since after that experience neither my family nor I returned to Canada until after I was an adult.

We had proper documentation (notarized permission letter, notarized copy of my birth certificate, passport)... The reason I say it's a Canadian neurosis (albeit semi-seriously) is that I made many other (25 or so) border crossings as a minor without parental accompaniment (many more with one parent), and never had an issue anywhere else (including Mexico, France, Italy, England, Austria, US, Switzerland, Cayman Islands).

I made at least 25 border crossings (mostly foreign-foreign) while a minor and not under the care of my parents or with a cousin who was not under the care of their parents (including a solo one to Mexico to meet up with some family friends when I was 10, although IIRC that was pretty paperwork heavy with the airline)... Canada was the only time there was any trouble.

Many years ago, when I was 6 or 7, my grandparents drove me up to Prince Edward Island for a vacation. Getting through the border into Canada took about 45 minutes, with my grandparents getting grilled and the agents asking me about a dozen times whether I wanted to be with them and whether my parents knew where I was etc etc.. Getting back into the US took about 2 minutes. It seems like it's a Canadian neurosis.

Both of the effects you describe are because the fovea has thicker ganglion cell density than non-foveal regions, which can induce a color bias over the several central degrees of your visual field. It's not 100% clear to me whether the GP is describing a visual hemifield effect, or an eye based effect (in the case of hemifields, each eye sends half its signal to each visual cortex)... but either way, it doesn't to me sound like a fovea-based bias.

(To clarify, by physical thing, I meant something that is both involuntarily induced, and non-constant)

I am a neuroscientist, mainly in vision, not an ophthalmologist.. but I have sat in on quite a bit of ophthalmology, done orbital dissections etc etc.. Very few physical things (ie. pressure based) can effect color perception. The main one is that you have something (either tumor, or spurious bone growth) that's pinching or entrapping your optic nerve (basically like carpel tunnel). If the same were happening to me, I'd make sure to get referred to an ophthalmology department at a research hospital and get a CAT scan to make sure nothing is growing behind the orbit.

That's mentioned in the IEEE Spectrum article (which by the way is about the most clearly written article on an early prototype technology that I've ever read).The problems are:-Too high voltage; can be mitigated by better geometry (probably).-Insufficient simulations at present for improving the geometry, with the caveat that getting better performance (voltage-wise) might compromise durability.-Because of the above, they don't have a good set of design rules to produce an integrated circuit. They're hopeful about this step, since the technique uses well established CMOS technology and there are many tools available.

Their next targets are things like gyroscopes and accelerometers. I'd say on the whole this strikes me as realistic and non-sensational. But if anybody knows better, I'd like to hear why.

This is no different from trying to come up with ways of measuring scholars' intellectual impact using citation metrics, like the h-factor or the many recent successors to it, which try to repair the weaknesses in a fatally flawed idea. It makes no distinction between positive and negative citation, and it ignores the raw fact of historical precedence, while preserving every historical bias a culture may have.

The most influential people in world history, at least the very top-tier, isn't particularly debatable, but yet this list failed to capture it. In alphabetical order (and assuming they all existed):

AristotleBuddhaConfuciusHomerJesusLao TzuMuhammadPlatoVed Vyasa

Then there's the next tier, which include people like Al-Hazan, Alexander, Augustine, Einstein, Genghis, Hammurabi, Imhotep, Newton, Linnaeus, Peter (of Russia), Shakespeare, Suleiman, Zeami Motokiyo etc etc, since I'm sure the further I try to extend the list, the more it would converge with my cultural history.

While unsupervised algorithms can often find interesting things in high-dimensional data, they aren't interpret-able without some expert knowledge.. and if you don't have the 9 entries I mentioned above in your top 20 at least, you can toss the method.

This is a well known weakness with back-propagation based learning algorithms. In the learning stage it's called Catastrophic interference, in the testing stage it manifests itself by mis-classifying similar inputs.

There's a huge bias towards using exclusively male mice in many types of research, and the issue of higher variance in female rodent behavior (due to estrous cycle issues, among others) is well known (see eg: pdf).

There are also related problems more generally with stress and over-training in neuroscience. Experienced investigators are able to produce a much less stressful working environment for animals, so they tend to get different results from neophyte investigators even when following the same protocol. This shows up a lot when a different lab tries to replicate the work of an experienced post-doc and gets null results for the first 6 months then suddenly is able to replicate everything. Thus often is attributed to 'correcting' the protocol (often with extensive communication with the previous lab) when often I think the change is attributable to the investigator in the replicating lab becoming experienced enough to relieve stress (I don't have a great link for this, mostly just an observation from having been around quite a few labs).

Over-training is also a problem, since it often takes thousands (sometimes well into the hundreds of) to train animals in complex cognitive tasks, and it's well known from experiments in humans (and a few in non-human primate and rodent) that neural responses shift profoundly between 'trained' and 'over-trained' states, say between amateur and professional ballerinas watching videos of ballet.

However, these issues are a much bigger problem in pre-clinical research than in basic research. Our understanding of the brain is sufficiently limited that the effects we're used to seeing in basic research questions swamp the potential modulation from gender, stress and training factors (unless you're talking about stress research specifically, but they're pretty careful about controlling for these types of effect). The issue with pre-clinical research is that often the difference between the current treatment and proposed treatment is only a few percent (note: if valid, this can mean thousands of lives saved or hugely improved), and so failing to identify and control for factors such as researcher or mouse gender can overwhelm the supposed primary result.

To destroy the world's carrying capacity for humanity we have to opt-in to global thermonuclear war. To destroy that same capacity through climate change simply requires that a modest proportion of the world's population does not opt-out of mitigating carbon release (the Pareto-optimal level of GDP is pretty small, actually, around 2% of global GDP).